Assistant Professor of Medicine
Kevin has a rare combination of skills from his prior undergraduate and PhD training, which encompasses both (wet-lab based) molecular genetic/epigenetic and (dry-lab) bioinformatics and biostatistics expertise. Kevin is working on advanced computational analysis using TCGA data.
Mu Zhou earned Ph.D. degree in Computer Science and Engineering, advised by Dr. Lawrence Hall and Dr. Dmitry Goldgof at the University of South Florida in 2015. His research interests are focused on the intersection of precision medicine and data mining. During his Ph.D. study, he has been involved in cross-disciplinary research projects, directed by Dr. Robert Gatenby and Dr. Robert Gillies at H. Lee. Moffitt Cancer Research Institute, Tampa. In particular, he worked on the field of quantitative cancer imaging for tumor response assessment in various domains (e.g., brain, breast, sarcoma, and lung cancers). His research aims to develop computational models that integrate clinical information (e.g., imaging, genomic, and clinical records) to predict cancer treatment outcomes and improve personalized healthcare.
Hong is a Postdoc in the Gevaert lab. Hong got her PhD from The University of Hong Kong, Department of Clinical Oncology, under the supervision of Prof. Maria Lung. She studied bioinformatics and cancer genomics and her thesis was on Identification of Genetic Susceptibility Genes and Characterization of Somatic Mutations in Nasopharyngeal Carcinoma. Her interests focus on big data in genomics and precision medicine. She works with multiple omics datasets, including whole-genome, whole-exome, transcriptome, methylome, etc. She is proficient in several programming languages (R, Python, Linux/Bash, and Perl), statistical analysis, and machine learning methods. Her research has been focused on understanding the genetic and genomic basic of cancer by integrating and digging into the massive amount of sequencing datasets in cancer genomics. Currently, she works on developing novel algorithms for high throughput sequencing data. She focuses on studying long non coding RNAs and epigenomics.
Haruka’s research has focused on imaging genomics in brain tumors. She has developed an approach that flips the common analysis framework, by starting from the imaging phenotype of a solid tumor instead of it’s molecular characterization. She has used quantitative characterizations of human brain tumors using their MR images to define subgroups. This led to three brain tumor subgroups that she successfully validated in an external validation data set and was able to match with molecular pathway activities. This result showed thought-provoking implicates with regards to treatment for brain tumors.
Lina is a graduate student in electrical engineering.
Clare is a graduate student in electrical engineering.
Marcos focuses on the statistical analysis of DNA methylation in cancer. He uses and extends, MethylMix, a method which identifies differentially methylated and transcriptionally predictive genes, in samples from single or combined cancer sites. He is currently pursuing a PhD in Buenos Aires, Argentina.
Shaimaa is a graduate student in electrical engineering working with Sandy Napel. Shaimaa is interested in quantitative imaging and radiogenomics of liver cancer.
Edward is a graduate student in electrical engineering in the Wong lab. He is interested in deep learning applications of medical imaging.
Majed is an undergrad at Stanford.
Raunaq is a master student at Stanford, interested in machine learning, in particular deep learning and bio-informatics.
Romain is a master student at Stanford.
Nathalie is an assistant professor at Harvard University and the Broad Institute.
Idoia is an Assistant Professor of Electrical and Computer Engineering.
Mikel is the Director of Computational Genomics at the IGB, University of Illinois
Adrien is an assistant professor at EPFL, Lausanne.
Murilo is a head and neck radiologists visiting from Sao Pualo Brazil. Murilo is interested in modeling head and neck cancers and how quantitative imaging can be used to diagnose and treat patients.
Chao Huang is a visiting student from Zhejiang University in Hangzhou supported by the China Scholarship Council. She is interested in biomedical data fusion and applying advanced statistics on large biomedical data.
Zichen Wang is a visiting student from Zhejiang University in Hangzhou. He is interested in machine learning analysis on quantitative image features and deep learning with applications to healthcare. His research focuses on developing deep learning models on pathology images.
Interns & past interns
Eleanor is a computer science major at UC Berkeley and she is interested in deep learning applications on brain tumor multi-modal imaging.
Natasha is an undergraduate at University of California Irvine. She is pursuing a B.S. in Biomedical Engineering and a minor in Bioinformatics. She is interested in applying computational skills to model and solve biological problems.
Anika Cheerla is a high school student at Monta Vista High School in Cupertino, CA
Nikhil Cheerla is an undergrad at Stanford university.
Shuo Wang is a student at the Chinese Academy of Sciences in Beijing.
Dondong Yu is a student at the Chinese Academy of Sciences in Beijing.
Katie finsihed her phd focusing on developing algorithms on meta-analysis of biomedical data. She developed CoINcIDE, a method for meta-clustering across multiple biomedical data sets. She currently is a co-founder & CTO at Mantra Bio.
Magali Champion was a postdoc in the lab focusing on the integration of multi-omics data for cancer investigation. She is currently continuing her postdoc studies at Paris Descartes.
Julie is focusing her medical studies on informatics and data driven medicine. She is intersted in how epigenomics defines subtypes of cancer patients and how this can impact precision medicine. She joined the lab as a Stanford Med Scholar, and after finishing continued her medical studies.